Making changes to your website without testing is like throwing darts in the dark—you might hit the target, but chances are, you won’t. That’s where testing methods like A/B testing and multivariate testing come in. Both help you make data-backed decisions, but they serve different purposes.
If you’ve ever wondered, “Should I run an A/B test or a multivariate test?” This guide will explain the differences so you can choose the right method based on your goals.
Understanding A/B Testing and Multivariate Testing
Before choosing one, it’s important to understand how they work.
What is A/B Testing?
A/B testing (or split testing) compares two webpage versions, emails, or ads to see which performs better.
- Version A (control): The original version
- Version B (variant): The modified version with one key change
The goal is to measure how a single change—like a new headline or a different button colour—affects user behaviour.
What is Multivariate Testing?
Multivariate testing is like A/B testing but takes it a step further. Instead of comparing just one change, it tests multiple changes at once to see which combination works best.
For example, if you’re testing a landing page, you might change:
- The headline
- The CTA button color
- The product image
Multivariate testing creates different versions that combine these changes in various ways to find the best-performing mix.
When to Use A/B Testing
A/B testing is the go-to method for most website experiments because it’s simple and effective.
Use A/B testing when:
- You want to test one change at a time (like a new CTA, different pricing display, or form length).
- You need clear and quick results without too much complexity.
- Your website doesn’t have high traffic—multivariate testing requires more visitors to be effective.
- You’re optimising a specific goal, such as increasing sign-ups or reducing cart abandonment.
Example:
You’re running an A/B test on your checkout page to compare:
Version A: “Complete Your Order” button in blue
Version B: “Place Order Now” button in red
At the end of the test, you’ll know which button gets more clicks.
When to Use Multivariate Testing
Multivariate testing is best when you want to test multiple elements at the same time and understand how they interact.
Use multivariate testing when:
- You have high website traffic—since multiple versions are being tested at once, you need more visitors to get reliable results.
- You want to test different combinations of changes to find the most effective setup.
- You’re redesigning a page with multiple elements, such as a homepage or landing page.
- You need to understand how changes work together rather than in isolation.
Example:
You’re testing a product page and changing three elements:
- Headline: “Best-Selling Laptop” vs. “Top-Rated Laptop”
- CTA Button Color: Green vs. Red
- Product Image: Angle view vs. Front view
This creates multiple versions of the page, and the test helps determine which combination drives the most conversions.
Key Differences Between A/B Testing and Multivariate Testing
| Feature | A/B Testing | Multivariate Testing |
| Number of Variants | Two (control vs. variant) | Multiple combinations |
| Complexity | Simple | More complex |
| Traffic Needed | Works for low to high-traffic | Requires high traffic |
| Testing Focus | One element at a time | Multiple elements at once |
| Best For | Clear, quick insights | Finding the best combination |
Choosing the Right Testing Method for Your Website
If you’re not sure which method to use, consider these questions:
- How much traffic do you have?
- If traffic is low to moderate, start with A/B testing.
- If traffic is high, multivariate testing might work.
- Are you testing a single change or multiple changes?
- A/B testing is best for a single change.
- Multivariate testing is better for multiple changes at once.
- Do you need quick results or deeper insights?
- A/B testing gives faster results.
- Multivariate testing gives detailed insights into element interactions but takes longer.
- Are you optimising an entire page or just one element?
- A/B testing is great for small but meaningful tweaks.
- Multivariate testing helps when designing complex pages with multiple elements.
How CustomFit.ai Makes Testing Easier
Running A/B and multivariate tests manually can be time-consuming, but CustomFit.ai helps simplify the process.
- Easily create tests without coding.
- Split traffic automatically between variations.
- Get real-time insights to track performance.
- Segment audiences for more accurate testing.
Whether you’re testing a simple headline change or optimizing an entire landing page, CustomFit.ai makes it easy to run experiments that lead to real improvements.
FAQs: A/B Testing vs. Multivariate Testing
1. Which testing method is better?
It depends on your goal. A/B testing is great for quick insights on single changes, while multivariate testing helps understand how multiple changes work together.
2. Can I run both A/B and multivariate tests on the same website?
Yes! Many businesses start with A/B testing and move to multivariate testing when they have more traffic and want deeper insights.
3. How long should I run an A/B or multivariate test?
A/B tests typically run for one to two weeks, while multivariate tests may need longer to gather enough data.
4. Does multivariate testing always give better results?
Not necessarily. If traffic is low, it might not generate statistically significant results, making A/B testing the better choice.
5. What’s the best thing to test first?
Start with A/B testing on high-impact elements like CTA buttons, headlines, and product images before moving to multivariate testing for larger redesigns.
Final Thoughts
Both A/B testing and multivariate testing help improve website performance, but choosing the right method depends on your traffic, testing goals, and available time.
- If you’re new to testing or have low traffic, A/B testing is the best place to start.
- If you have high traffic and want to experiment with multiple elements, multivariate testing can provide deeper insights.
No matter which method you choose, testing is about learning what works best for your audience.
Want an easier way to run both A/B and multivariate tests? Try CustomFit.ai and start optimizing your website today.
